{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["8(11)"],"submitter":["Kou W"],"pubmed_abstract":["<h4>Introduction</h4>Gastric cancer (GC) is one of the most common malignant tumors worldwide. Single-cell sequencing technology can achieve an accurate and unbiased assessment of cell heterogeneity. Therefore, it is necessary to explore the molecular characteristics of GC-related malignant cells at a single-cell resolution.<h4>Methods</h4>Single-cell RNA sequencing GC profiles were collected from the Gene Expression Omnibus database. Moreover, feature gene sets of metabolic pathways and hypoxia signals were collected from the Molecular Signatures Database. The marker genes of specific cell types were collected from the published literature and CellMarker database. The R package InferCNV was used to calculate the copy-number variations of cells and to identify real cancer cells. The weight"],"journal":["Heliyon"],"pagination":["e11866"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9713346"],"repository":["biostudies-literature"],"pubmed_title":["Single-cell characterization revealed hypoxia-induced metabolic reprogramming of gastric cancer."],"pmcid":["PMC9713346"],"pubmed_authors":["Zhao N","Li H","Zhao L","Qiao C","Zhang L","Wang Y","Kou W","Song J","Yin Z","Zhang MC"],"additional_accession":[]},"is_claimable":false,"name":"Single-cell characterization revealed hypoxia-induced metabolic reprogramming of gastric cancer.","description":"<h4>Introduction</h4>Gastric cancer (GC) is one of the most common malignant tumors worldwide. Single-cell sequencing technology can achieve an accurate and unbiased assessment of cell heterogeneity. Therefore, it is necessary to explore the molecular characteristics of GC-related malignant cells at a single-cell resolution.<h4>Methods</h4>Single-cell RNA sequencing GC profiles were collected from the Gene Expression Omnibus database. Moreover, feature gene sets of metabolic pathways and hypoxia signals were collected from the Molecular Signatures Database. The marker genes of specific cell types were collected from the published literature and CellMarker database. The R package InferCNV was used to calculate the copy-number variations of cells and to identify real cancer cells. The weight","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Nov","modification":"2026-05-10T03:08:56.392Z","creation":"2025-02-19T04:15:10.073Z"},"accession":"S-EPMC9713346","cross_references":{"pubmed":["36468095"],"doi":["10.1016/j.heliyon.2022.e11866"]}}